Computational and Statistical Methods for Protein Quantification by Mass Spectrometry

Name: Computational and Statistical Methods for Protein Quantification by Mass Spectrometry
Brand: Wiley
SKU: 9781119964001
Price: 10889.0 INR
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by Ingvar Eidhammer

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ISBN13: 9781119964001
Binding: Hardcover
Subject: N/A
Publisher: Wiley
Publisher Imprint: Wiley
Publication Date: February 11, 2013
Pages: 334
Original Price: USD 119.95
Language: English
Edition: N/A
Item Weight: 567 grams
BISAC Subject(s): Probability & Statistics / General

About The Book

The definitive introduction to data analysis in quantitative proteomics

This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers.

Computational and Statistical Methods for Protein Quantification by Mass Spectrometry:

*Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs. *Is illustrated by a large number of figures and examples as well as numerous exercises. *Provides both clear and rigorous descriptions of methods and approaches. *Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work. *Features detailed discussions of both wet-lab approaches and statistical and computational methods.

With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.

About The Author

Ingvar Eidhammer, Department of Informatics, University of Bergen, Norway

Harald Barsnes, Department of Biomedicine, University of Bergen, Norway

Geir Egil Eide, Centre for Clinical Research, Haukeland University, Norway

Lennart Martens, Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Belgium

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